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2023
Yijun Zhang, Ziyi Yin, Oscar Lopez, Ali Siahkoohi, Mathias Louboutin, and Felix J. Herrmann, “3D seismic survey design by maximizing the spectral gap”, in International Meeting for Applied Geoscience and Energy, 2023.
Mathias Louboutin, Rafael Orozco, Ali Siahkoohi, and Felix J. Herrmann, “Learned non-linear simultenous source and corresponding supershot for seismic imaging.”, in International Meeting for Applied Geoscience and Energy, 2023.
2022
Mathias Louboutin, Philipp A. Witte, Ali Siahkoohi, Gabrio Rizzuti, Ziyi Yin, Rafael Orozco, and Felix J. Herrmann, “Accelerating innovation with software abstractions for scalable computational geophysics”, in International Meeting for Applied Geoscience and Energy Expanded Abstracts, 2022.
Ziyi Yin, Ali Siahkoohi, Mathias Louboutin, and Felix J. Herrmann, “Learned coupled inversion for carbon sequestration monitoring and forecasting with Fourier neural operators”, in International Meeting for Applied Geoscience and Energy Expanded Abstracts, 2022.
Ali Siahkoohi, Gabrio Rizzuti, Rafael Orozco, and Felix J. Herrmann, “Reliable amortized variational inference with conditional normalizing flows via physics-based latent distribution correction”, in IMAGE Workshop on Subsurface Uncertainty Description and Estimation - Moving Away from Single Prediction with Distribution Learning, 2022.
Yijun Zhang, Mathias Louboutin, Ali Siahkoohi, Ziyi Yin, Rajiv Kumar, and Felix J. Herrmann, “A simulation-free seismic survey design by maximizing the spectral gap”, in International Meeting for Applied Geoscience and Energy Expanded Abstracts, 2022.
Ali Siahkoohi, Mathias Louboutin, and Felix J. Herrmann, “Velocity continuation with Fourier neural operators for accelerated uncertainty quantification”, in International Meeting for Applied Geoscience and Energy Expanded Abstracts, 2022.
2021
Rajiv Kumar, Maria Kotsi, Ali Siahkoohi, and Alison Malcolm, “Enabling uncertainty quantification for seismic data pre-processing using normalizing flows (NF)—an interpolation example”, in SEG Technical Program Expanded Abstracts, 2021, pp. 1515-1519.
Ali Siahkoohi and Felix J. Herrmann, “Learning by example: fast reliability-aware seismic imaging with normalizing flows”, in SEG Technical Program Expanded Abstracts, 2021, pp. 1580-1585.
2020
Gabrio Rizzuti, Ali Siahkoohi, Philipp A. Witte, and Felix J. Herrmann, “Parameterizing uncertainty by deep invertible networks, an application to reservoir characterization”, in SEG Technical Program Expanded Abstracts, 2020, pp. 1541-1545.
Mi Zhang, Ali Siahkoohi, and Felix J. Herrmann, “Transfer learning in large-scale ocean bottom seismic wavefield reconstruction”, in SEG Technical Program Expanded Abstracts, 2020, pp. 1666-1670.
Ali Siahkoohi, Gabrio Rizzuti, and Felix J. Herrmann, “Uncertainty quantification in imaging and automatic horizon tracking—a Bayesian deep-prior based approach”, in SEG Technical Program Expanded Abstracts, 2020, pp. 1636-1640.
Ali Siahkoohi, Gabrio Rizzuti, and Felix J. Herrmann, “Weak deep priors for seismic imaging”, in SEG Technical Program Expanded Abstracts, 2020, pp. 2998-3002.
2019
Ali Siahkoohi, Rajiv Kumar, and Felix J. Herrmann, “Deep-learning based ocean bottom seismic wavefield recovery”, in SEG Technical Program Expanded Abstracts, 2019, pp. 2232-2237.
Ali Siahkoohi, Dirk J. Verschuur, and Felix J. Herrmann, “Surface-related multiple elimination with deep learning”, in SEG Technical Program Expanded Abstracts, 2019, pp. 4629-4634.
2018
Ali Siahkoohi, Mathias Louboutin, Rajiv Kumar, and Felix J. Herrmann, “Deep Convolutional Neural Networks in prestack seismic–-two exploratory examples”, in SEG Technical Program Expanded Abstracts, 2018, pp. 2196-2200.